Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly, non-destructive, and non-open-world, so the safety profile is covered. The description adds genuine behavioral context beyond that: the output is evidence rather than approval, and per-asset attribution should not be fabricated. That tells the agent how to treat the results, not just that the call is safe.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences with no filler, and the scope statement is front-loaded before the caveat. The phrasing of the caveat ('no invented per-asset attribution') is terse enough to be slightly cryptic, but nothing is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a nested-body diagnostics tool with no output schema and two-thirds of parameters undocumented, the description does not explain the shape or meaning of the result, what distinguishes 'policy' coverage from 'observed' coverage, or what the date range controls. Annotations cover safety but the functional gaps remain large.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 33% — just customer_id ('10-digit Google Ads customer id'). The nested body fields (campaign_id, date_from, date_to) and connection_context carry no description in either the schema or the tool description, and the description contributes no parameter meaning at all, so it fails to compensate for the low coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The verb ('Read') and resource area ('policy and observed asset coverage evidence with campaign metrics') are stated, so an agent knows this is a read-oriented diagnostics call. However, 'coverage evidence' is abstract jargon and the description never differentiates it from close siblings such as google_ads_asset_inventory_list or google_ads_asset_requirements_get. The agent can guess the domain but not what it actually returns.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use statement and no named alternative among the many asset-related siblings. The only guidance present ('Missing policy is not approval') is an interpretation caveat about the data, not a condition for selecting this tool over another.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.